ArticleAnnals of the American Thoracic Society2026
Oncologic and physiologic predictors of mortality after intensive care unit admission in patients with lung cancer.
Article in Annals of the American Thoracic Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between elevated multiple circulating biomarkers and short-term mortality in critically ill lung cancer patients: a meta-analysis.Frontiers in oncology · 2026Pooled it
- Prognostic Role of Nutritional and Inflammatory Indices in Predicting Adverse Clinical Outcomes in Unplanned Hospitalized Oncology Patients.Journal of clinical medicine · 2026Article
- Construction and validation of a prognostic prediction model for critically ill lung cancer patients based on respiratory functional reserve and systemic inflammatory characteristics.American journal of cancer research · 2026Article
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8 authors.
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Abstract
rationaleCritically ill lung cancer patients are a growing, high-risk population. However, prognostic tools to guide intensive care unit (ICU) decision-making are limited.
objectivesTo identify oncologic and critical illness factors associated with 90-day mortality following ICU admission in patients with lung cancer.
methodsWe conducted a retrospective cohort study of lung cancer patients admitted to the ICU across Mayo Clinic Health System between 2018 and 2024. The primary outcome was 90-day mortality. Two complementary Cox proportional hazards models were developed: a focused model including cancer-specific variables (stage, time since diagnosis, time since last systemic therapy, prior thoracotomy, Eastern Cooperative Oncology Group [ECOG] performance status prior to admission, body mass index, cause of critical illness, code status at admission) and a full model that added broader clinical factors (age and Sequential Organ Failure Assessment [SOFA] score). We also evaluated discharge disposition and transitions in code status.
resultsAmong 528 patients, 90-day mortality was 58.7%. In the focused model (C-index 0.67), independent predictors of mortality included late-stage disease, cancer-specific reason for ICU admission, limitations in resuscitation orders, and ECOG >1. In the full model (C-index 0.95), only age and SOFA score remained significant. Among early-stage patients, recent targeted or combination therapy was associated with higher mortality, though this association may reflect underlying disease characteristics or treatment selection rather than direct treatment effects. Patients who changed code status during admission had high mortality (83%) and a low rate of discharge home (11%).
conclusionLung cancer patients admitted to ICU experience high short-term mortality, with outcomes shaped by both oncologic status and the severity of acute illness. A dual-model approach suggests a risk hierarchy: Cancer-specific factors inform baseline mortality risk with an ICU admission, but age and physiologic derangement are the dominant drivers of survival once critical illness develops. These findings support dynamic, multidisciplinary prognostication and underscore the need to integrate oncology and critical care expertise in ICU decision-making.
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